How Hasura’s GraphQL schema generation works

Given your Postgres database, Hasura GraphQL engine can automatically generate a GraphQL schema and process both GraphQL queries and mutations.

How does Hasura GraphQL engine know which tables and views are in which schema and how to connect them so that they form a graph over which queries and mutations should be allowed?

Here’s what Hasura GraphQL engine does under the hood:


Let’s say you have a table, a profile (id, name) table, in Postgres that you want to expose over GraphQL.

All you need to do is tell Hasura GraphQL engine to track this table, and Hasura GraphQL engine automatically generates a GraphQL schema with:

  1. A GraphQL type definition for the table
  2. Queries with where, order_by, limit and offset arguments
  3. Insert mutations that support bulk and upsert
  4. Update mutations that support conditional bulk updates
  5. Delete mutations that support conditional bulk deletes


If you have a view in Postgres, Hasura GraphQL engine does the same thing it would for a table, but without creating mutations.

Relationships or Connections

Between one table/view and another table/view, you can tell Hasura GraphQL engine to create a relationship or a connection between their 2 nodes in a graph, using a particular column as a link. Often, you have foreign-key constraints that indicate a relationship and you can tell Hasura GraphQL engine to use that foreign-key constraint to create a relationship too.

You can specify an object relationship or an array relationship between tables and views. For example:

  1. You might have a restaurant.average_rating where average_rating is a view connected to the restaurant table via a restaurant_id.
  2. You might have a user.addresses where each user has multiple addresses connected via a user_id.

When you create a relationship, Hasura GraphQL engine does the following:

  1. Augments the types of tables/views involved by adding a reference to the nested type
  2. Augments the possible where and order_by clauses that can be used to enable nested filtering and sorting


Hasura GraphQL engine does not have any resolvers. The Hasura GraphQL engine is actually a compiler that compiles your GraphQL query into an SQL query. Hasura’s GraphQL syntax is also optimized to expose the power of the underlying SQL so that you can make powerful queries via GraphQL.


All the metadata required for the above is stored by Hasura GraphQL engine in specific Postgres schemas in your database. See Hasura GraphQL engine internals for details.